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Distilling your data into valuable information

Posted on 26 May 2015.

Analogy between a whisky distillery and data management

The similitudes don’t typically jump out, do they? But you’ll quickly see the point.

On one side, in a whisky distillery we have engineers who build the tubings and alembics and such (the containers), and biologists who are in charge of taking care of the many processes leading to the final product (the content). It’s all about measuring the quality and tasting.

Once bottled, the blend of whisky goes to meet the world (and be enjoyed by happy consumers).

On the other side we have computer scientists who take care of databases and application programs (the containers) and users fill them with data (the content).

But who takes care of the data?

Developers will point out that data is the end user’s problem and users will argue that data is the developers’ business. When they’re both fully concerned.

An example in numbers to illustrate the fact that data should be everyone’s business in an organization :

A bank (among Rever's clientele) has calculated that the data management part done by the users has a cost of €80 per customer.
This bank having more than 10,000,000 customers, an astronomic €800,000,000 was spent to fill its databases.
In the sole purpose of being able to do the job. And strangely enough no one seems to feel responsible for this legacy...

To continue with our distillation analogy, tasting the flavour of data is complex because they are stored in separate applications in different silos. Under these conditions it’s hard, if not impossible, to integrate and measure the quality of data in order to draw value from them.

Rever Data Engineers’ tools will allow you to build the “tubings” that will handle your data the way you wish, as the distillery does with its finest malts, in order to produce a nice blend of knowledge. And as everybody knows, knowledge is power.

We are distilling your data since 2004

We constantly come up with new creative ideas that have the potential to change data management as we know it.